Basic concepts of data analysis and statistical inference, applied to
1-sample and 2- sample location problems, the analysis of variance,
and linear regression. Probability models and statistical methods
applied to practical situations and actual data sets from various
disciplines. Elementary statistical theory, including the plug-in
principle, maximum likelihood, and the method of least squares.
S520 provides a strong introduction to elementary statistical
methodology and a gentle introduction to elementary statistical
theory. It meets concurrently with S320, but includes supplementary
material not covered in that course. S520 introduces material that is
covered in greater depth in S620 (Introduction to Statistical Theory),
but less mathematically and in the context of actual experiments and
data. It fulfills the theory requirement for the M.S. degree in
Applied Statistics (currently under review).